U.S. Navy is developing target-tracking ‘smart bullets’ to defend against drone swarms

By Nicole Carpenter Published January 18, 2017

Now that drones are used by most modern militaries, swarm attacks are a very real threat to the United States Navy. But not to worry — the The U.S. Defense Advanced Research Projects Agency (DARPA) has a solution for that: smart bullets.

DARPA recently announced an $8 million contract with Raytheon Missile Systems to enter phase two of its Multi Azimuth Defense Fast Intercept Round Engagement System (MAD-FIRES) program. As part of the deal, Raytheon will build and test MAD-FIRES bullets that are able to alter their path in real time, according to Military Aerospace. Additionally, they’ll be able to track and engage with multiple targets with serious precision from a variety of different directions.

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Concepts and simulations of the technology were completed during the first phase, which also included Lockheed Martin Corp. Missiles and Fire Control. Lockheed will likely receive a contract to conduct their own prototyping rounds, too.

MAD-FIRES smart bullets are expected to be fast, powerful, and have the same accuracy as regular missiles, using 20 to 40 caliber ammunition. So even if attacks from drones, missiles, planes, or swarm boats are coming from all different directions, the MAD-FIRES bullets could potentially take all of them out.

The Navy is also working with the Office of Naval Research to develop unmanned swarm boats designed to patrol U.S. shores. As with its MAD-FIRES bullets, the swarm boat program is part of the Navy’s increased efforts to embrace technological advances. Unmanned swarm boats reduce risk, while MAD-FIRES bullets offer a new, low-cost solution for “guided, gun-launched projectiles.”

Raytheon’s phase two is scheduled to finish in March 2018. So while the concept of “smart bullets’ seems like something you’d only see in the movies, it seems that it’s not as far-fetched as you might think.

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Nicole Carpenter

Former Digital Trends Contributor

Nicole is a freelance video game and tech writer from Massachusetts. She has a cat named Puppy.

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“One feedback we’ve heard loud and clear is that customers love [Highway Assist] but they want to use it in more places,” James Philbin, Rivian VP of autonomy, said on the podcast RivianTrackr Hangouts. “So that’s something kind of exciting we’re working on, we’re calling it internally ‘Map Free’, that we’re targeting for later this year.”
The lag between the release of Highway Assist (HWA) and Map Free automated driving gives time for the fleet of Rivian vehicles to gather ‘unique events’. These events are used to train Rivian’s offline model in the cloud before data is distilled back to individual vehicles.
As Rivian founder and CEO RJ Scaringe explained in early March, HWA marked the very beginning of an expanding automated-driving feature set, “going from highways to surface roads, to turn-by-turn.”
For now, HWA still requires drivers to keep their eyes on the road. The system will send alerts if you drift too long without paying attention. But stay tuned—eyes-off driving is set for 2026.
It’s also part of what Rivian calls its “Giving you your time back” philosophy, the first of three pillars supporting Rivian’s vision over the next three to five years. Philbin says that philosophy is focused on “meeting drivers where they are”, as opposed to chasing full automation in the way other automakers, such as Tesla’s robotaxi, might be doing.
“We recognize a lot of people buy Rivians to go on these adventures, to have these amazing trips. They want to drive, and we want to let them drive,” Philbin says. “But there’s a lot of other driving that’s very monotonous, very boring, like on the highway. There, giving you your time back is how we can give the best experience.”
This will also eventually lead to the third pillar of Rivian’s vision, which is delivering Level 4, or high-automation vehicles: Those will offer features such as auto park or auto valet, where you can get out of your Rivian at the office, or at the airport, and it goes off and parks itself.
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